Electrical conduction and relaxation mechanism in Li<Subscript>2</Subscript>AlZr[PO<Subscript>4</Subscript>]<Subscript>3</Subscript>

Li-ion electrolyte NASICON type Li₂AlZr[PO₄]₃ has been prepared by Solid State Reaction method. Formation of the sample has been confirmed by XRD and TGA–DTA analysis. Electrical conductivity studies have been performed in the frequency range 42 Hz–5 MHz within the temperature range 523–623 K using aluminium as blocking electrodes. The conductivity has been found to be 1 × 10⁻⁵ S cm⁻¹ at 623 K. Dielectric spectra show the decrease in dielectric constant with increase in frequency. Dielectric loss spectra reveal that dc conduction contribution predominates in the sample. Spectroscopic plots of complex modulus suggest the Non-Debye behaviour of the electrical relaxation within the temperature range studied.     

Lie group analysis of radiation natural convection heat transfer past an inclined porous surface

Natural convection heat transfer fluid flow past an inclined plate embedded in a fluid-saturated porous medium is investigated by Lie group analysis. The governing partial differential equations are reduced to a system of ordinary differential equations by the scaling symmetries. From numerical results, it is found that the thermal and momentum boundary layer thicknesses are increased as the radiation parameter is increased. Also, it is observed that the velocity is increased and the temperature is decreased for increasing the buoyancy parameter and the porosity parameter.     

Natural Convection in a Porous Cavity with Sinusoidal Heating on Both Sidewalls

A numerical study has been performed on buoyancy-induced convection in a square porous cavity. The vertical sidewalls of the cavity are maintained with sinusoidal temperature distribution. The finite volume method is used to numerically solve the nondimensional governing equations. The Brinkman Forchheimer extended Darcy model is used in the present study. The results are analyzed over a range of the amplitude ratio, phase deviation, porosity, and Grashof and Darcy numbers. It is found that the heat transfer rate is increased when increasing the amplitude ratio, porosity, and Darcy number. The nonuniform heating on both sidewalls provides higher heat transfer rate than the nonuniform heating of one wall.     

A Stable and Intelligent Energy-Efficient Solid-State Induction Motor Controller

A three-phase AC voltage controller can be used for energy saving while feeding a lightly loaded induction motor. In this paper, while optimizing the power consumed by the motor, the sampling time ( Delta t) and the step change in firing angle ( Delta alpha) have been appropriately chosen by simulating the transient performance of the system using the simulation language SIMNON. A combination of current minimization scheme and power factor maximization scheme has been advocated here which yields better savings than the constituent schemes individually. A functional relationship between the optimum value of alpha ( alpha opt) and the load on the motor has been deduced so that for a given load the same optimum point is attained always in spite of the inaccuracies in the current sensing mechanism. The hardware implementation is based on an Intel 8085 processor. The processor develops this functional relationship (AngleLoad Pattern) by learning the system behavior for two or more different load conditions. Thus, it can intelligently adapt itself to any variations in the system parameters because of temperature rise or other nonlinearities.     

Adaptive and optimal control of a non-linear process using intelligent controllers

A time-optimal control for set point changes and an adaptive control for process parameter variations using neural network for a non-linear conical tank level process are proposed in this work. Time-optimal level control was formulated using dynamic programming algorithm and basic properties of the solutions were analysed. It was found that the control is of bang–bang type and there is only one switching. In this method, a mathematical step-by-step procedure is used to obtain the optimal valve position path with one switching and is trained by neural network, based on the back-propagation algorithm. The dynamic programming procedure allows the set point to be reached as fast as possible without overshoot. An adaptive system is also designed and proved to be useful in adjusting the trained parameter of the dynamic programming based neural network for the process parameter variations. A prototype of conical tank level system has been built and implementation of dynamic programming based neural network control algorithm for set point changes and implementation of adaptive control for process parameter variations are performed. Finally, the performance is compared with conventional control. The results prove the effectiveness of the proposed optimal and adaptive control schemes.     

P/G Pin Position-Aware Voltage Island Floorplanning For IR Drop Security and avoidance in Flip Chip Designs of FIR Filter

In flip-chip design, voltage drop reduction in the power ground network has become a challenging problem particularly in the modern Multiple Supply Voltage(MSV) designs. An effective P/G network design and floorplanning- based solutions helps to produce a quality power plan in the layout. Hence, this paper proposes an iterative MSV floorplanning methodology that performs modifications in the existing floorplan representation that satisfies the voltage island constraint and produce an IR drop-aware quality layout. Furthermore, the proposed methodology is integrated with commercial tool design flow to analyze the reduction of IR drop in the layout. Two simulation-based experiments are performed in this paper to showcase the significance of this work. Firstly, it presents the simulation results that benchmark the proposed idealogy in non-flip chip designs. Secondly, the presented framework is integrated in flip-chip layouts of FIR design operating with two voltage islands for low power consumption. To understand the ability of the proposed floorplanning approach, the simulation were performed for two different sized P/G mesh structure for various mesh width. Experimental results from both simulations demonstrate that the proposed MSV floorplanning technique is effective in reducing IR drop while optimizing the design for low power dissipation.

     

Scheduling and resources allocation in network traffic using multiobjective,multiuser joint traffic engineering

Wireless Networks - Reciprocal optimality is a desirable characteristic from the end user perspective, for both Best Effort and Quality of Service (QoS) datagrams delivery within a network. A...     

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

Abstract

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.     

Magneto-convection of nanofluids in a lid-driven trapezoidal cavity with internal heat generation and discrete heating

The present work investigates numerically the effect of an inclined magnetic field on the mixed convection flow in a trapezoidal enclosure in the presence of internal heat generation or absorption. The trapezoidal enclosure is filled with water-based nanofluid containing copper nanoparticles. Both the inclined left and right walls are adiabatic. A heat source with constant heat flux placed on the bottom wall of the enclosure and the remaining portions are thermally insulated. The top wall of the enclosure is maintained at a constant low temperature and is moving with a constant speed in its own plane from left to right. The governing equations are discretized by the control volume method and are solved numerically by the SIMPLE algorithm. A parametric study is performed and a set of graphical results is presented and discussed to demonstrate the interesting features of the solution.     

Completely biodegradable banana fiber-wheat gluten composites for dielectric applications

Biodegradable composites with desirable dielectric constants were obtained using banana fibers as reinforcement and wheat gluten as matrix. Dielectric materials play a critical role in many integrated circuits and microelectronics. Most dielectric materials are made from ceramics and synthetic polymers which are heavy, expensive, have limited range of dielectric values and also not biodegradable. Unlike previous reports that have developed partially biodegradable composites for dielectric applications, we have used protein and a natural fiber as matrix and reinforcement, respectively resulting in composites that are completely biodegradable. In addition, the thickness of the composites was varied which creates air gaps and influences the dielectric properties. Mechanical and electrical properties of the composites were studied at ambient and higher temperatures. Flexural and tensile properties were significantly influenced by the ratio of matrix and reinforcement and thickness of the composites. Dielectric values obtained ranged from 2 to 49 depending on the frequency. Dielectric constant, dielectric loss and dissipation factor decreased whereas conductivity increased with increasing frequency for all the samples. Biodegradable composites suitable for various electronic applications can be obtained with desired dielectric values by varying the composite fabrication conditions.